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        If you use plots from MultiQC in a publication or presentation, please cite:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

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        Tool Citations

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        About MultiQC

        This report was generated using MultiQC, version 1.22.2

        You can see a YouTube video describing how to use MultiQC reports here: https://youtu.be/qPbIlO_KWN0

        For more information about MultiQC, including other videos and extensive documentation, please visit http://multiqc.info

        You can report bugs, suggest improvements and find the source code for MultiQC on GitHub: https://github.com/MultiQC/MultiQC

        MultiQC is published in Bioinformatics:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

        A modular tool to aggregate results from bioinformatics analyses across many samples into a single report.

        Report generated on 2024-06-05, 21:28 CEST based on data in: /home/pascal/Documents/git_projects/grifo/src_0.6/multiqc

        NanoStat

        NanoStat reports various statistics from a long read sequencing dataset in FASTQ, BAM or sequencing summary format.DOI: 10.1093/bioinformatics/bty149.

        Summary Statistics

        Showing 3/3 rows and 5/7 columns.
        Sample NameMedian lengthRead N50Median Qual# Reads (K)Total Bases (Mb)
        barcode01_statreports
        631bp
        632bp
        11.1
        25.0K
        16.1Mb
        barcode02_statreports
        639bp
        640bp
        11.1
        26.7K
        17.3Mb
        barcode03_statreports
        642bp
        643bp
        11.1
        20.9K
        13.7Mb

        Reads by quality

        Read counts categorised by read quality (Phred score).

        Sequencing machines assign each generated read a quality score using the Phred scale. The phred score represents the liklelyhood that a given read contains errors. High quality reads have a high score.

        Created with MultiQC

        MultiQC v1.22.2 - Written by Phil Ewels, available on GitHub.

        This report uses Plotly, jQuery, jQuery UI, Bootstrap, FileSaver.js and clipboard.js.